Class Imbalance in FSL has received some attention, although the current work is not comprehensive [1]}, [2]}, [3]}, [4]}. We identify that in FSL, class-imbalance occurs at two levels: the task-level and the meta-dataset level. At the task level, class-imbalance occurs in the support set or the query-set, directly affecting the learning and evaluation procedures. At the meta-dataset level, class-imbalance occurs in the class distribution used for task-sampling and representation learning. In Figure REF , we highlight the differences between imbalanced task and imbalanced meta-dataset.
Related to, but distinct from, these two imbalance types is task-distribution imbalance [3]}, where the underlying task-distribution seen during meta-training is different from meta-evaluation task-distribution. In extreme cases, task-distribution imbalance can lead to out-of-distribution tasks during meta-evaluation. Task-distribution imbalance has already received some attention [3]}, [7]} and it will only be discussed tangentially in this work.
